Field Performance Prediction and IR Imaging Simulation Based on Measured System Level Parameters*

Abstract

Traditionally, the Minimum Resolvable Temperature Difference (MRTD) and the Johnson criteria are used to predict the field performance of IR imaging system. However this method generally leads to far too pessimistic range predictions. For the improvement of the prediction accuracy of the field performance, a novel approach to predict field performance is proposed based on the three-dimensional infrared scene generated by Vega software. Further, this approach utilizes the measured system level parameters to characterize the signal transfer process, noise, and the blur effect of the output image instead of theoretical model. By controlling the target range in the simulated image, a simulation experiment is performed, and the range corresponding to the 75% correct probability of discrimination is achieved by the statistical method. Comparisons with the real experimental result show that this method can give more accurate range prediction than the target acquisition (TA) model based on the MRTD.